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UID:20251101T232129EDT-6580Lu8Rmt@132.216.98.100
DTSTAMP:20251102T032129Z
DESCRIPTION:Jessica Myers Franklin\, PhD\n\nAssistant Professor\, Medicine\
 , Harvard Medical School & Biostatistician\, Division of Pharmacoepidemiol
 ogy and Pharmacoeconomics\, Brigham and Women’s Hospital\n\nComparing marg
 inal estimators of propensity-adjusted treatment effects in studies with f
 ew observed outcome events\n\nAbstract:\n\nNonrandomized studies of treatm
 ents from electronic healthcare databases are critical for producing the e
 vidence necessary to making informed treatment decisions\, but often rely 
 on comparing rates of events observed in a small number of patients. In ad
 dition\, a typical study constructed from an electronic healthcare databas
 e\, for example\, administrative claims data\, requires adjustment for man
 y\, possibly hundreds\, of potential confounders. Despite the importance o
 f maximizing efficiency when there are many confounders and few observed o
 utcome events\, there has been relatively little research on the performan
 ce of different propensity score methods in this context. In this talk\, I
  will describe and compare a wide variety of propensity-adjusted estimator
 s of the marginal relative risk. In contrast to prior research that has fo
 cused on specific statistical methods in isolation of other analytic choic
 es\, I instead consider a method to be defined by the complete multi-step 
 process from propensity score modeling to final treatment effect estimatio
 n. I evaluate methods via a “plasmode” simulation study\, which creates si
 mulated data sets based on a real cohort study of 2 treatments constructed
  from administrative claims data. Our results suggest a reconsideration of
  the most popular approaches to propensity score adjustment in this contex
 t.\n\nBio:\n\nwww.drugepi.org/faculty-staff-trainees/faculty/jessica-frank
 lin/\n
DTSTART:20160202T203000Z
DTEND:20160202T213000Z
LOCATION:Room 24\, Purvis Hall\, CA\, QC\, Montreal\, H3A 1A2\, 1020 avenue
  des Pins Ouest
SUMMARY:Biostatistics Seminar
URL:/epi-biostat-occh/channels/event/biostatistics-sem
 inar-257553
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